Maximize Workforce Capacity with RPA

Any task that is repetitive, rules-based and takes place within typically static frameworks (such as software or a website with a format that rarely changes) is a candidate for RPA. If a worker can easily break down their process into a series of steps involving software interactions, you can probably build a robot to replicate that process.

RPA robots don’t make decisions; they follow rules. If the rules break or bend, bots break down, too. Tasks that require complex decision-making and the ability to handle exceptions aren’t ideal for RPA. However, they can be suitable for other forms of automation through a comprehensive intelligent automation platform.

No: Artificial intelligence and machine learning are separate but adjacent technologies to RPA. Some forms of business automation, such as conversational chatbots, blend elements of RPA with AI. However, even those use cases represent the intersection of technologies working together, not necessarily AI-powered RPA.

Think of RPA as a foundation for intelligent automation. Robots can often represent an easy pathway to initial automation “wins” through a low barrier to entry. As you integrate RPA into your organization, the integration may reveal shortcomings in processes that you weren’t aware of previously. That revelation can start the process of your business embracing additional intelligent automation tools and the transformation of how you do business. At Kofax, we call this breakthrough in true digital transformation “working like tomorrow,” where companies begin to use automation to work smarter across the entire organization.

There are many common reasons why an RPA deployment fails. Lack of sufficient buy-in from key business stakeholders and participants due to a poor understanding of RPA’s benefits is one frequent reason for failure. Choosing the wrong platform, an error-prone bot development process and poor post-deployment oversight can all lead to undesirable outcomes.

Yes, but it is a challenge for many businesses. A robust RPA platform that streamlines every step, from process discovery and bot building to performance oversight and review, will contribute to more robust opportunities for scale. Remember that if a task seems too big for RPA, there are other options.

No—in fact, RPA functions at its best when it works alongside humans to empower workers to deliver more high-value work. A common RPA use case is automatically fetching customer account data so that customer service representatives can efficiently help a larger number of clients. RPA hasn’t replaced the rep in this example. Instead, it has taken over less-valuable but still fundamental duties.

Deploying RPA always starts with identifying automation opportunities and educating your colleagues on the benefits of such an investment. When a project gets the greenlight, a multi-stage lifecycle process combined with the right platform choices will allow you to launch your first bot within weeks or months.

RPA, or robotic process automation, delivers new levels of efficiency by using software to perform tedious and repetitive tasks normally done by humans. With this digital workforce carrying out their instructions, humans are free to focus on higher value tasks, such as engaging with customers. RPA works best for high volume task workflows with highly defined, rules-based processes and clear endpoints.

These robots interact with software interfaces as a human would and bring multiple potential benefits to business users. Costly errors and typos that create confusion are easy to eliminate with bots that always enter data correctly. Optimized and scaled RPA can reduce business operating costs and open the door to more advanced intelligent automation solutions as your business gains experience.